Investigating backtranslation for the improvement of English-Irish machine translation

In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for...

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Main Authors: Meghan Dowling, Teresa Lynn, Andy Way
Format: Article
Language:English
Published: The Irish Association for Applied Linguistics 2019-11-01
Series:Teanga: The Journal of the Irish Association for Applied Linguistics
Subjects:
Online Access:https://journal.iraal.ie/index.php/teanga/article/view/88
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author Meghan Dowling
Teresa Lynn
Andy Way
author_facet Meghan Dowling
Teresa Lynn
Andy Way
author_sort Meghan Dowling
collection DOAJ
description In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.
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spelling doaj.art-38299098bf4c45b88d8a8f498e67713e2022-12-22T00:15:15ZengThe Irish Association for Applied LinguisticsTeanga: The Journal of the Irish Association for Applied Linguistics0332-205X2565-63252019-11-012610.35903/teanga.v26i0.88Investigating backtranslation for the improvement of English-Irish machine translationMeghan Dowling0Teresa Lynn1Andy Way2ADAPT Centre, Dublin City UniversityADAPT Centre, Dublin City UniversityADAPT Centre, Dublin City UniversityIn this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.https://journal.iraal.ie/index.php/teanga/article/view/88Machine translationBacktranslationIrish languageAutomatic Evaluation Metrics
spellingShingle Meghan Dowling
Teresa Lynn
Andy Way
Investigating backtranslation for the improvement of English-Irish machine translation
Teanga: The Journal of the Irish Association for Applied Linguistics
Machine translation
Backtranslation
Irish language
Automatic Evaluation Metrics
title Investigating backtranslation for the improvement of English-Irish machine translation
title_full Investigating backtranslation for the improvement of English-Irish machine translation
title_fullStr Investigating backtranslation for the improvement of English-Irish machine translation
title_full_unstemmed Investigating backtranslation for the improvement of English-Irish machine translation
title_short Investigating backtranslation for the improvement of English-Irish machine translation
title_sort investigating backtranslation for the improvement of english irish machine translation
topic Machine translation
Backtranslation
Irish language
Automatic Evaluation Metrics
url https://journal.iraal.ie/index.php/teanga/article/view/88
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AT teresalynn investigatingbacktranslationfortheimprovementofenglishirishmachinetranslation
AT andyway investigatingbacktranslationfortheimprovementofenglishirishmachinetranslation